Impulse Noise (audio)
Impulse noise is a category of (acoustic) noise which includes
unwanted, almost instantaneous (thus impulse-like) sharp sounds (like
clicks and pops). Noises of the kind are usually caused by
electromagnetic interference, scratches on the recording disks,
gunfire, explosions and ill synchronization in digital recording and
communication. High levels of such a noise (200+ decibels) may damage
internal organs, while 180 decibels are enough to destroy or damage
human ears.
An impulse noise filter can be used to enhance the quality of noisy
signals, in order to achieve robustness in pattern recognition and
adaptive control systems. A classic filter used to remove impulse
noise is the median filter, at the expense of signal degradation
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Crackling NoiseCrackling noiseCrackling noise arises when a system is subject to an external force
and it responds via events that appear very similar at many different
scales. In a classical system there are usually two states, on and
off. However, sometimes a state can exist in between. There are three
main categories this noise can be sorted into: the first is popping
where events at very similar magnitude occur continuously and
randomly, e.g. popcorn; the second is snapping where there is little
change in the system until a critical threshold is surpassed, at which
point the whole system flips from one state to another, i.e. snapping
a pencil; the third is crackling which is a combination of popping and
snapping, where there are some small and some large events with a
relation law predicting their occurrences, referred to as
universality.[1] Crackling can be observed in many natural phenomena,
e.g
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AcousticsAcousticsAcoustics is the branch of physics that deals with the study of all
mechanical waves in gases, liquids, and solids including topics such
as vibration, sound, ultrasound and infrasound. A scientist who works
in the field of acoustics is an acoustician while someone working in
the field of acoustics technology may be called an acoustical
engineer. The application of acoustics is present in almost all
aspects of modern society with the most obvious being the audio and
noise control industries.
HearingHearing is one of the most crucial means of survival in the animal
world, and speech is one of the most distinctive characteristics of
human development and culture. Accordingly, the science of acoustics
spreads across many facets of human society—music, medicine,
architecture, industrial production, warfare and more
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Phase Distortion
In signal processing, phase distortion or phase-frequency distortion
is distortion, that is, change in the shape of the waveform, that
occurs when (a) a filter's phase response is not linear over the
frequency range of interest, that is, the phase shift introduced by a
circuit or device is not directly proportional to frequency, or (b)
the zero-frequency intercept of the phase-frequency characteristic is
not 0 or an integral multiple of 2π radians.
Audibility of phase distortion[edit]
Grossly changed phase relationships, without changing amplitudes, can
be audible but the degree of audibility of the type of phase shifts
expected from typical sound systems remains debated.[1][2][3]
See also[edit]Audio system measurements
Phase noiseReferences[edit]^ Arthur C Ludwig Sr. (1997). "Audibility of Phase Distortion".
Retrieved 15 February 2016.
^ Lipshitz, Stanley P.; Pocock, Mark; Vanderkooy, John (1 September
1982)
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Gaussian NoiseGaussian noiseGaussian noise is statistical noise having a probability density
function (PDF) equal to that of the normal distribution, which is also
known as the Gaussian distribution.[1][2] In other words, the values
that the noise can take on are Gaussian-distributed.
The probability density function p displaystyle p of a Gaussian random variable z displaystyle z is given by: p G (
z
)
= 1 σ 2
π
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Record Restoration
Record restoration, a particular kind of audio restoration, is the
process of converting the analog signal stored on gramophone records
(either 78 rpm shellac, or 45 and 33⅓ rpm vinyl) into digital audio
files that can then be edited with computer software and eventually
stored on a hard-drive, recorded to digital tape, or burned to a CD or
DVD. The process may be divided into several separate steps performed
in the following order:
1. Cleaning the record, to prevent unwanted audio artefacts from being
introduced in the capture that will necessitate correction in the
digital domain (e.g. transient surface noise caused by dirt), and to
prevent unnecessary wear and damage to the stylus used in playback. 2.
Transcription of the record to another format on another medium
(generally a digital format such as a wav file on a computer);
3
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Audio Synchronizer
An audio synchronizer is a variable audio delay used to correct or
maintain audio-video sync or timing[1] also known as lip sync error.
See for example the specification for audio to video timing given in
ATSC Document IS-191.[2] Modern television systems use large amounts
of video signal processing such as MPEG preprocessing, encoding and
decoding, video synchronization and resolution conversion in pixelated
displays. This video processing can cause delays in the video signal
ranging from a few microseconds to tens of seconds. If the television
program is displayed to the viewer with this video delay the
audio-video synchronization is wrong, and the video will appear to the
viewer after the sound is heard
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Pink NoisePink noisePink noise or ​1⁄f noise is a signal or process with a frequency
spectrum such that the power spectral density (energy or power per
frequency interval) is inversely proportional to the frequency of the
signal. In pink noise, each octave (halving/doubling in frequency)
carries an equal amount of noise energy. The name arises from the pink
appearance of visible light with this power spectrum.[1] This is in
contrast with white noise which has equal intensity per frequency
interval.
Within the scientific literature the term pink noise is sometimes used
a little more loosely to refer to any noise with a power spectral
density of the form S
(
f
)
∝ 1 f α , displaystyle S(f)propto frac 1 f^ alpha , where f is frequency, and 0 < α < 2, with exponent α usually
close to 1
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Median Filter
The median filter is a nonlinear digital filtering technique, often
used to remove noise from an image or signal. Such noise reduction is
a typical pre-processing step to improve the results of later
processing (for example, edge detection on an image).
MedianMedian filtering
is very widely used in digital image processing because, under certain
conditions, it preserves edges while removing noise (but see
discussion below), also having applications in signal processing.Contents1 Algorithm description
2 Worked 1D example
3 Boundary issues
4 2D median filter pseudo code
5 Algorithm implementation issues
6 Edge preservation properties
7 See also
8 References
9 External linksAlgorithm description[edit]
The main idea of the median filter is to run through the signal entry
by entry, replacing each entry with the median of neighboring entries.
The pattern of neighbors is called the "window", which slides, entry
by entry, over the entire signal
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Decibel
The decibel (symbol: dB) is a unit of measurement used to express the
ratio of one value of a physical property to another on a logarithmic
scale. It can be used to express a change in value (e.g., +1 dB
or −1 dB) or an absolute value. In the latter case, it
expresses the ratio of a value to a reference value; when used in this
way, the decibel symbol should be appended with a suffix that
indicates the reference value or some other property. For example, if
the reference value is 1 volt, then the suffix is "V" (e.g, "20 dBV"),
and if the reference value is one milliwatt, then the suffix is "m"
(e.g., "20 dBm").[1]
There are two different scales used when expressing a ratio in
decibels depending on the nature of the quantities: field, power, and
root-power
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Gunfire
A gunshot is a single discharge of a gun, typically a man-portable
firearm, producing a visible flash, a powerful and loud shockwave and
often chemical gunshot residue. The term can also refer to a ballistic
wound caused by such a discharge.
Multiple discharges of one or more firearms are referred to as
gunfire. The word can connote either the sound of a gun firing, the
projectiles that were fired, or both. For example, the statement
"gunfire came from the next street" could either mean the sound of
discharge, or it could mean the bullets that were discharged. It is
better to be a bit more specific while writing however. "The sound of
gunfire" or "we came under gunfire" would be more descriptive and
prevent confusion. In the latter phrase, in particular, "fire" is more
commonly used (i.e
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Electromagnetic InterferenceElectromagnetic interferenceElectromagnetic interference (EMI), also called radio-frequency
interference (RFI) when in the radio frequency spectrum, is a
disturbance generated by an external source that affects an electrical
circuit by electromagnetic induction, electrostatic coupling, or
conduction.[1] The disturbance may degrade the performance of the
circuit or even stop it from functioning. In the case of a data path,
these effects can range from an increase in error rate to a total loss
of the data.[2] Both man-made and natural sources generate changing
electrical currents and voltages that can cause EMI: ignition systems,
cellular network of mobile phones, lightning, solar flares, and
auroras (Northern/Southern Lights)
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Impulse Function
In mathematics, the Dirac delta function, or δ function, is a
generalized function, or distribution that was historically introduced
by the physicist
Paul DiracPaul Dirac for modelling the density of an idealized
point mass or point charge, as a function that is equal to zero
everywhere except for zero and whose integral over the entire real
line is equal to one.[1][2][3] As there is no function that has these
properties, the computations that were done by the theoretical
physicists appeared to mathematicians as nonsense, until the
introduction of distributions by Laurent Schwartz, for formalizing and
validating mathematically these computations
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Gradient NoiseGradient noise is a type of noise commonly used as a procedural
texture primitive in computer graphics. It is conceptually
different[further explanation needed], and often confused with value
noise. This method consists of a creation of a lattice of random (or
typically pseudorandom) gradients, dot products of which are then
interpolated to obtain values in between the lattices. An artifact of
some implementations of this noise is that the returned value at the
lattice points is 0. Unlike the value noise, gradient noise has more
energy in the high frequencies.
The first known implementation of a gradient noise function was Perlin
noise, credited to Ken Perlin, who published the description of it in
1985. [1] Later developments were
Simplex noise and OpenSimplex noise.References[edit]^ David Ebert, Kent Musgrave, Darwyn Peachey, Ken Perlin, and Worley.
Texturing and Modeling: A Procedural Approach. Academic Press, October
1994
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